Method for optimizing a descent trajectory of an aircraft based on selected meteorological data

ABSTRACT

A method of descent trajectory of an aircraft includes an iterative process of selecting meteorological data points along a predicted descent trajectory, generating a wind profile along the predicted descent trajectory for the selected data points, determining a subset fuel cost and a subset time cost based upon the wind profile, selecting the subset that minimizes weighted fuel burn and time error, and calculating an optimized descent trajectory based on the selected subset.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/027,759 filed Feb. 15, 2011, and is incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention is related to selecting meteorological data, e.g.,wind and temperature data relevant to an aircraft's descent trajectory,and updating the aircraft trajectory based on the selected data. Morespecifically, the invention relates to producing and providing a smallersubset of relevant meteorological data from which an aircraft's descenttrajectory can be optimized.

Meteorological data at way points along an aircraft trajectory are oftenconsidered for determining an estimated time of arrival and fuel burnduring an aircraft's flight. For example, a flight management system(FMS) might consider wind velocity and temperature data uploaded to theFMS from a ground station via a communications system while the aircraftis in flight. The volume of such meteorological data typically is greatand can be provided along many points in the aircraft trajectory.However, limitations in available memory and available bandwidth oftenhamper the amount and timing of uploaded meteorological data. Such datais often provided to the FMS of an aircraft at the start point, the endpoint, and perhaps one or a few way points along the aircraft'strajectory. Many times the way points between the start point and theend point are selected based upon the location of ground navigation aids(Navaids) along the trajectory of the aircraft.

Limits in the data can compromise the accuracy of FMS forecasts based onthe data. As well, an aircraft is occasionally given a clearance toalter its trajectory en route, which results in a need to quickly updateforecasts, sometimes without planned waypoints. Many longer flights willhave long legs in cruise with no waypoints and no way for the data toaccount for weather changes between planned waypoints. For example,changes in wind velocity and direction during a long cruise withoutupdated data during that leg can result in errors in the forecastedwind, and thus in the time of arrival computations.

BRIEF DESCRIPTION OF THE INVENTION

A method of optimizing a descent trajectory of an aircraft comprisingthe steps of, in a processor: receiving a predicted descent trajectorycomprising a plurality of points including a start point and an endpoint; receiving meteorological information for data points along thepredicted descent trajectory; determining a fuel cost and time costbased upon the meteorological data points along the non-level predicteddescent trajectory; determining if the number of meteorological datapoints exceeds a predetermined maximum and if the number does not exceedthe predetermined maximum, then selecting all of the meteorological datapoints storing in a non-transitory medium the selected meteorologicaldata points as the second subset of meteorological data; removingredundant meteorological data points from the wind data at all of theplurality of points along the predicted descent trajectory; selecting asubset of the meteorological data containing the predetermined maximumnumber of data points from the plurality of wind data points along thepredicted descent trajectory; generating a wind profile along thepredicted descent trajectory using the subset of the meteorologicaldata; determining a subset fuel cost and a subset time cost based uponthe wind profile and recording the subset data points, the subset fuelcost and subset time cost; determining if a predetermined maximum numberof subsets have been selected and if the predetermined maximum number ofsubsets have not been selected, then selecting a subset again;determining a weighted fuel burn and time error based on the fuel cost,the time cost and the subset fuel cost and subset time cost for each ofthe subsets examined; selecting the meteorological data pointscorresponding to the subset that minimizes the weighted fuel burn andtime error; storing in a non-transitory medium the selectedmeteorological data points as the second subset of meteorological data;and calculating in the processor an optimized descent trajectory basedon the stored second subset.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings:

FIG. 1 is a schematic illustration of a ground station to aircraftcommunications system that can execute one embodiment of the presentinvention.

FIG. 2 is a schematic illustration of a flight trajectory to which themethods according to one embodiment of the present invention can beapplied.

FIG. 3 is a flow chart depicting selecting a subset of wind velocity andtemperature data according to one embodiment of the present invention.

FIG. 4 is a schematic illustration of the flight trajectory of FIG. 2showing inserted pseudo-way points along with forecasted wind profiles.

FIG. 5 is a flow chart depicting selecting wind and temperature dataselection for a level segment of a flight trajectory.

FIG. 6 is a flow chart depicting selecting wind and temperature dataselection for a non-level segment of a flight trajectory.

FIG. 7 depicts wind data at various elevations demonstrating theelimination of redundant wind.

DETAILED DESCRIPTION OF THE INVENTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the technology described herein. It will be evident toone skilled in the art, however, that the exemplary embodiments may bepracticed without these specific details. In other instances, structuresand device are shown in diagram form in order to facilitate descriptionof the exemplary embodiments.

The exemplary embodiments are described below with reference to thedrawings. These drawings illustrate certain details of specificembodiments that implement the module, method, and computer programproduct described herein. However, the drawings should not be construedas imposing any limitations that may be present in the drawings. Themethod and computer program product may be provided on anymachine-readable media for accomplishing their operations. Theembodiments may be implemented using an existing computer processor, orby a special purpose computer processor incorporated for this or anotherpurpose, or by a hardwired system.

As noted above, embodiments described herein include a computer programproduct comprising machine-readable media for carrying or havingmachine-executable instructions or data structures stored thereon. Suchmachine-readable media can be any available media, which can be accessedby a general purpose or special purpose computer or other machine with aprocessor. By way of example, such machine-readable media can compriseRAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magneticdisk storage or other magnetic storage devices, or any other medium thatcan be used to carry or store desired program code in the form ofmachine-executable instructions or data structures and that can beaccessed by a general purpose or special purpose computer or othermachine with a processor. When information is transferred or providedover a network or another communication connection (either hardwired,wireless, or a combination of hardwired or wireless) to a machine, themachine properly views the connection as a machine-readable medium.Thus, any such a connection is properly termed a machine-readablemedium. Combinations of the above are also included within the scope ofmachine-readable media. Machine-executable instructions comprise, forexample, instructions and data, which cause a general purpose computer,special purpose computer, or special purpose processing machines toperform a certain function or group of functions.

Embodiments will be described in the general context of method stepsthat may be implemented in one embodiment by a program product includingmachine-executable instructions, such as program code, for example, inthe form of program modules executed by machines in networkedenvironments. Generally, program modules include routines, programs,objects, components, data structures, etc. that have the technicaleffect of performing particular tasks or implement particular abstractdata types. Machine-executable instructions, associated data structures,and program modules represent examples of program code for executingsteps of the method disclosed herein. The particular sequence of suchexecutable instructions or associated data structures represent examplesof corresponding acts for implementing the functions described in suchsteps.

Embodiments may be practiced in a networked environment using logicalconnections to one or more remote computers having processors. Logicalconnections may include a local area network (LAN) and a wide areanetwork (WAN) that are presented here by way of example and notlimitation. Such networking environments are commonplace in office-wideor enterprise-wide computer networks, intranets and the internet and mayuse a wide variety of different communication protocols. Those skilledin the art will appreciate that such network computing environments willtypically encompass many types of computer system configuration,including personal computers, hand-held devices, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,minicomputers, mainframe computers, and the like.

Embodiments may also be practiced in distributed computing environmentswhere tasks are performed by local and remote processing devices thatare linked (either by hardwired links, wireless links, or by acombination of hardwired or wireless links) through a communicationnetwork. In a distributed computing environment, program modules may belocated in both local and remote memory storage devices.

An exemplary system for implementing the overall or portions of theexemplary embodiments might include a general purpose computing devicein the form of a computer, including a processing unit, a system memory,and a system bus, that couples various system components including thesystem memory to the processing unit. The system memory may include readonly memory (ROM) and random access memory (RAM). The computer may alsoinclude a magnetic hard disk drive for reading from and writing to amagnetic hard disk, a magnetic disk drive for reading from or writing toa removable magnetic disk, and an optical disk drive for reading from orwriting to a removable optical disk such as a CD-ROM or other opticalmedia. The drives and their associated machine-readable media providenonvolatile storage of machine-executable instructions, data structures,program modules and other data for the computer.

Technical effects of the method disclosed in the embodiments includeminimizing the communication costs of aircraft flight while increasingthe accuracy of the winds and temperatures used in trajectoryprediction, thereby increasing the accuracy of a predicted trajectory byan aircraft. It also can be used to minimize the time and fuel penaltyof the predicted trajectory, especially a descent trajectory.

FIG. 1 depicts a system 1 for aircraft-ground communication of the typein which the invention is used. An aircraft 20 may communicate with aground station 10 by way of a communication link 30. The communicationlink 30 may be any variety of communication mechanisms including but notlimited to packet radio and satellite uplink. In particular, theaircraft 20 has a flight management system (FMS) (not shown) on boardthat can communicate with the ground station 10 via the communicationlink 30. The FMS will generally have a limited amount of memoryavailable for storing meteorological data related to the flighttrajectory of the aircraft 20. The ground station 10 can be any type ofcommunicating ground station 10 such as air traffic control. In general,the communications link 30 will have limited bandwidth available fortransmitting extensive meteorological data related to the flighttrajectory of the aircraft 20, and, in any event, it can be costly tocommunicate large amounts of digital data via the communications link30. Although any type of information can be communicated via thecommunications link 30, this embodiment pertains specifically tocommunicating meteorological data to the aircraft 20.

FIG. 2 illustrates a predicted flight trajectory 44 overlaid on ageographic map 40, in this instance, of the United States. The predictedtrajectory 44 comprises a starting point 46 and an ending point 48 andfor purposes of this embodiment of the invention, comprises a levelsegment 50 (sometimes also known as a cruise segment) and a non-levelsegment 54. The level portion of the predicted trajectory 50 comprises alevel segment start point 46 that is the same start point as thepredicted trajectory 44, a level portion end point 58, and one or moreplanned way points 60 that are typically ground Navaids. The non-levelsegment 54 comprises a non-level segment start point 58, which can bethe same point as the level segment end point 58 and a non-level segmentend point 48, which can be the same point as the predicted trajectoryend point 48.

Although in the predicted trajectory 44 is shown to have one levelsegment 50 and one non-level segment 54 in FIG. 2, the predictedtrajectory can have any number of level segments and non-level segments.There may be multiple level segments and non-level segments, especiallyfor transcontinental flights where an aircraft may change it elevationto take advantage of or minimize the impact of prevailing winds, such asthe jet stream, to climb to higher altitudes as fuel is burned, or toavoid turbulence.

In general, there is likely to be at least one non-level segment 54corresponding to the descent during landing of the aircraft 20. Such adescent and, therefore, the non-level segment start point 58 may beapproximately 70 miles from the predicted trajectory end point 48. Thetake-off portion or the ascending portion of the predicted trajectory 44to achieve a level cruise altitude is generally short, and for purposesof this embodiment, is incorporated with the level segment 50. In accordwith this embodiment of the invention, the level segment 50 may furthercomprise one or more pseudo-way points 70. Pseudo-way points areartificial reference points created for some purpose relevant to aparameter of the trajectory. They can be defined by an air crew or viacommunications link 30 and not limited to ground navigation aids. Theycan be defined while en route after established way points for thetrajectory have been set. Further, pseudo-waypoints can be defined invarious ways, such as by latitude and longitude or by a specifieddistance along the current trajectory, such as an along-track way point.

The predicted trajectory 44 can be described in a three dimensional (3D)space as a three dimensional trajectory (3DT), or in a four dimensional(4D) space as a four dimensional trajectory (4DT). The three dimensionsof 3DT include latitude, longitude, and altitude. The four dimensions of4DT include latitude, longitude, altitude, and time. In other words, a4DT description of the aircraft trajectory defines where in 3D space theaircraft 20 is at any given point of time.

In this embodiment, meteorological data associated with the levelsegment 50 is provided to the FMS as a spatial definition of the waypoints 60 and 70 along with tailwind, cross-wind, and temperature data.The spatial definition of the way points 60 and 70 comprise alatitudinal and longitudinal coordinate of the waypoint. The tailwind isthe wind component that is parallel with the trajectory 44 of theaircraft 20 at any point along the trajectory 44. Similarly, thecross-wind is the wind component in a direction perpendicular to thetrajectory 44 of the aircraft 20 at any point along the trajectory 44.It should be noted that headwind, which is a negative value of thetailwind, may also be used instead of tailwind without detracting fromthe disclosure herein.

Also in this embodiment, meteorological data associated with thenon-level portion 54 is provided to the FMS of the aircraft 20 as anelevation point, wind speed, wind direction, and temperature. The FMStypically converts wind speed and wind direction into cross wind andtail wind components.

The meteorological data can be sent to the FMS of the aircraft 20 forboth the level 50 and non-level 54 segments concurrently or separatelyvia communications link 30. Although the meteorological data comprisestailwind, cross-wind, and temperature elements for both segments 50 and54, the meteorological data may comprise greater or fewer elements. Forexample, the meteorological data may only comprise tailwind andcross-wind components, without temperature data. As an alternativeexample, the meteorological data can comprise tailwind, cross-wind,temperature, humidity, and barometric pressure data elements.

Accurate, timely, and appropriate meteorological data should beavailable during the entire trajectory to enable accurate prediction ofevents related to the trajectory. For example, in the level segment 50it is desirable to have appropriate meteorological data such that thefuel burn and estimated time of arrival are accurately determined. In anon-level segment 54 such as descent, there is a trend in the aviationindustry to use a green approach, which necessitates accurate andup-to-data meteorological data to build an accurate 4D trajectory toreduce fuel burn during the descent and landing of the aircraft 20. Withappropriate meteorological data for a non-level segment 54 such asdescent and landing, fuel usage can be optimized.

In accord with this embodiment of the invention, FIG. 3 depicts a method100 of selecting an appropriate subset of available meteorological datafor transmission to an aircraft 20 via communications link 30 tofacilitate a more accurate forecast of events related to the trajectory44. The method 100 generates meteorological data for the FMS of theaircraft 20 or other user of the data, pertaining to the predictedtrajectory 44 in either or both level 50 and non-level 54 segments. Themethod 100 starts with the predicted trajectory 44 being received at102. Next, wind and temperature data for a region containing thepredicted trajectory 44 is received at 104. All of the temperature andwind velocity data for the predicted trajectory 44 of the aircraft isfiltered at 106. In other words, only the data relevant to theaircraft's 20 predicted trajectory 44 is retained for further selectionin subsequent steps. It is then determined at 108 if the predictedtrajectory 44 of the aircraft has a level segment 50. If so, then thelevel segment 50 wind and temperature data is determined at 110, a stepdescribed in greater detail in conjunction with FIG. 5. If not, or ifthe level segment 50 wind and temperature data is determined at 110, themethod 100 then proceeds at 112 to determine if the predicted trajectory44 has a non-level segment 54. If so, then non-level segment wind andtemperature data is determined at 114, a step described in greaterdetail in conjunction with FIG. 6. If not, or if the non-level segment54 wind and temperature data is determined at 114, the method 100 thenproceeds at 116 to store and/or send all of the wind and temperaturedata to the aircraft or other user of the data. At 116 the data storedand/or sent can include wind and temperature data for a level segmentonly, a level segment and a non-level segment, or for a non-levelsegment only, depending on the decisions made at steps 108 and 112.

Referring now to FIG. 4, the addition of pseudo-waypoints 70 along thelevel segment 50 of the predicted trajectory 44, and the resultingimprovements in determining the wind profile are graphically depicted.The two-dimensional depiction of the level segment of the trajectory 50as shown in FIG. 2 is projected in FIG. 4 onto a single dimension tobetter view the implications of inserting pseudo-way points 70 betweenthe level segment start point 46 and the level segment end point 58.Points 120, 122, and 124 represent wind velocity data at the levelsegment start point 46, the planned way point 60, and the end point 58,respectively. The wind data can comprise any type of wind dataincluding, but not limited to, tailwind, cross-wind, wind velocity, winddirection, headwind or combinations thereof. The wind data can beinterpolated between each of these points 120, 122, and 124 to generatea wind profile 126 for the level segment 50. The wind profile 126comprises a first interpolated segment of wind data 128 between levelsegment start point 46 and level segment waypoint 60 and a secondinterpolated segment of wind data 130 between the level segment waypoint60 and the level segment end point 58. As discussed before, there issome question about the accuracy of the wind profile 126 through eachinterpolated segment 128, 130.

In accord with this embodiment of the invention, evaluating a windprofile 140 with pseudo-waypoints 70 includes additional wind data 132,134, and 136 corresponding to pseudo-waypoints 70 that can result ingreater accuracy than the wind profile 126 without pseudo-waypoints. Ineffect, for the wind profile 140 with pseudo-waypoints, theinterpolation between points is conducted over shorter distances withinterpolation segments 142, 144, 146, 148, and 150. Interpolation overlarger distances such as wind profile 126 without pseudo-waypoints canintroduce error in the prediction of wind data as can clearly be seenwhen comparing with wind profile 140 with pseudo-waypoints. For example,in the path between the level segment start point 46 and the firstpseudo-waypoint 70, the interpolated segment 142 contains wind data thatdiffers from the wind data over the same distance in the interpolatedsegment 128. Such discrepancies exist when comparing the interpolationsegments 144 to 128, 146 to 128, 148 to 130, and 150 to 130. Therefore,it is seen that non-negligible error in the predicted wind data isavoided by interpolating over shorter distances with additionalpseudo-waypoints 70 along the level segment 50.

To minimize errors associated with interpolating wind data over longdistances, the method 110 is described in FIG. 5 to select the mostappropriate pseudo-waypoints 70 with associated wind and temperaturedata along the level segment 50. First, at 160 the level segment 50trajectory of the aircraft is received or predicted. This can entailreceiving the overall trajectory 44 and determining the level segment 50from that trajectory data. As mentioned earlier, the trajectory can bedescribed as 4DT or 3DT, without detracting from the inventive conceptsdisclosed herein.

At 162, wind and temperature information for a region containing thelevel segment 50 is also received. Like level segment trajectory 50, thewind and temperature information can be in any known format, such as 2D(latitude and longitude), 3D (latitude, longitude, and altitude), or 4D(latitude, longitude, altitude, and time). The wind information cancomprise any known type of information, including wind velocityincluding wind speed and wind direction.

Once the wind information is received at 162, the method 110 nextdetermines the tailwind and cross-wind at every point along the levelsegment at 164 from the wind information. The derivation may be by anyknown method. In one aspect, the tailwind may be derived from aninstantaneous trajectory of the aircraft 20 and the known wind velocityas follows:

TW=WS*cos(φ),

Where TW is the tailwind,

WS is the wind speed, and

φ is the angle between the aircraft trajectory and the wind direction.

Similarly, the cross-wind may be derived as follows:

CW=WS*sin(φ),

Where CW is the crosswind.

The derivation of the tailwind and the cross wind may be betterunderstood by way of example. If an aircraft has an instantaneousdirection of due north and the wind velocity at that location and timeis 20 knots wind speed (WS) due northeast, then the angle (φ) betweenthe instantaneous aircraft 20 direction and the wind direction is 45°and therefore the tailwind (TW) is 14.1 knots (20*cos(45°)) and thecrosswind (CW) is also 14.1 knots (20*sin(45°)).

The points along the level segment 50 can be of any resolution.Furthermore, it is possible that the points along the level segment 50may be of variable resolution, especially for international flights andmore especially for transcontinental flights. For example, in a flightbetween the United States and Europe, there may be a finer resolution ofwind information (and therefore the derived wind data) for points overland in the United States and Europe, for example wind data every 2 km,and a reduced resolution for points over the Atlantic Ocean.

Continuing now with method 110, each succeeding point along the levelsegment 50 is stepped to and the difference in the wind gradient isdetermined at that point at 166. The wind gradient can be determined bysubtracting current wind data from the previous wind data and dividingby the distance. For example, the tailwind gradient can be determined bysubtracting the tailwind at the current point along the level segment 50from the tailwind at the previous point along the level segment anddividing by the distance from the previous point to the current point.It is understood that a gradient and difference in wind gradient may notbe determined for the start point of the level segment 46, as there isno previous wind data point to consider at that point along the levelsegment 50.

At 168, it is determined if the level segment end point 58 is reached.If not, then it is determined if the difference between the windgradient at the current point and the wind gradient at the previouspoint satisfies a threshold at 170. Satisfying a threshold can mean thatthe wind gradient is greater than a predetermined value. For example,the predefined gradient threshold can be 15 knots/km. In that case, achange in the tailwind or the headwind (opposite direction of thetailwind) of greater than 15 knots over 1 km would satisfy thethreshold.

If at 170 it is determined that the difference in the gradient at thecurrent point satisfies the threshold, then the current point is definedas a pseudo-waypoint at 172 and the method 110 returns to 166 toconsider the next point along the level segment 50. If at 170 it isdetermined that the difference in the gradient at the current point doesnot satisfy the threshold, then the method 110 returns to 166 toconsider the next point along the level segment 50.

If at 168 it was determined that the level segment end point 58 isreached, then the method 110 jumps to 174 and steps to the firstwaypoint. At this point of the method 110 all of the necessary pseudowaypoints 70 have been defined in the execution of the loop consistingof 166, 168, 170, and 172. Next, the method 110 retrieves the wind andtemperature data at the current waypoint at 176. At 178, it isdetermined if the last waypoint has been reached. If so, then the method110 stores all of the wind data, temperature date and the associatedwaypoint locations at 180. This data can optionally be sent to the FMSof aircraft 20 or other users of the data. If at 178 it is determinedthat the last waypoint was not reached, then the method returns to 174to address the next waypoint.

It should be noted that at 172 there may be a number of pseudo-waypointsdefined that exceed a maximum waypoint threshold. This may especially betrue if the level segment is relatively long or if the wind gradientthreshold is set too low. In such a case, the method 110 canautomatically increase the wind gradient threshold and rerun elements166 to 172 or the method can simply select the pseudo-waypoint locationswith the greatest wind gradient.

It is seen that the method 110 defines the locations along the levelsegment 50 where pseudo-waypoints 70 are inserted based upon gradient orstepwise change in relevant wind data such as tailwind data. By usingthe gradient of the relevant wind data for data selection,pseudo-waypoints are effectively inserted at points where there isgreatest impact in reducing errors resulting from creating a windprofile by interpolating with too few waypoints. The data that is storedat 180 and sent to the FMS of the aircraft 20 includes the location ofthe pseudo-waypoint and the meteorological data, such as wind speed,wind direction, and temperature for each pseudo-waypoint 70 as well aseach planned waypoint 60. The data can be sent as two separate uplinktransmissions where the location of the waypoints are sent first andthen the wind data is sent.

Referring now to FIGS. 6 and 7, a method 114 of selecting non-levelsegment wind and temperature data is illustrated. First the predictednon-level segment trajectory 54 is received at 190. Next, wind andtemperature information containing the predicted non-level segment 54 isreceived at 192. For the non-level segment 54, the wind and temperatureinformation can be in any known format, such as 2D (latitude andlongitude), 3D (latitude, longitude, and altitude), or 4D (latitude,longitude, altitude, and time). The wind information can comprise anyknown type of information, including wind velocity and wind direction.

At 194, relevant meteorological data is calculated at every point alongthe non-level segment 54. Generally, this data will include tailwinddata and cross-wind data. The calculation of tail wind and cross-winddata from meteorological information such as wind velocity has beendescribed above for the level segment 50 in conjunction with element 164of method 110. A fuel and time cost is also determined at 194 based uponthe meteorological data determined at every point along the non-levelsegment 54. The fuel cost can be a function of the estimated fuel burn,such as a linear scaling of the fuel burn. The time cost can be afunction of the total time to arrive at the non-level segment end point48, such as a linear scaling of the total time to arrival. A time costand fuel cost is generally used instead of a just the time and fuel tohave a non-unit method of comparing the two parameters on the samescale. For example, if a non-level segment nominally lasts for 20minutes and consumes 600 lbs. of fuel, then an appropriate fuel cost maybe equal to estimated fuel usage divided by 600 lbs. and an appropriatetime cost may be equal to the non-level segment time divided by 20minutes.

At 196, it is determined if the number of wind elements is greater thana predetermined MAX element threshold. The MAX element threshold is asystem limited threshold or user defined threshold that defines themaximum number of data sets (altitude along with meteorological data)that can be sent to the FMS or other user of the meteorological data.Thus, if the number of wind elements calculated at 194 does not exceedthe MAX elements threshold, then all of the computed wind data set canbe selected and can be stored at 198 for sending to the FMS or otheruser of the wind data. The selected data set can, for example, be storedin electronic memory of a computer system used to carry out the method114 and can subsequently be transmitted to the aircraft 20 viacommunications link 30.

It is expected, however, that the number of elements calculated at 194will exceed the MAX element threshold at 196 because a typical FMSsystem can generally accept approximately 5 elements and there may be 50or more elements calculated at 194. Consequently, a subset of the windelements calculated at 194 is preferably selected to minimize error inthe predicted time of arrival and fuel burn.

The selection of the wind elements involves removal of redundant windelements at 200. A data set for the non-level segment 54 is defined byan altitude and related meteorological data (tailwind, cross-wind, andtemperature) at that altitude. To remove redundant wind elements at 200,the method 114 can disregard data associated with altitudes where thereis no change in relevant wind data. It further illustrates this conceptby way of example in FIG. 7 showing a plot of relevant wind data versusaltitude 220. In this example, the relevant wind data can be tailwinddata with tailwind elements 222, 224, 226, 228, 230, 232, 238, 240, 242,244, 246, 248, and 250 and headwind (negative tailwind) elements 234 and236. The relevant wind data can vary with elevation, but there may be arange of elevations where the relevant wind data does not varyappreciably with elevation as seen with data points 242, 244, 246, and248, as well as, data points 222, 224, 226, 228. Such phenomena ofminimal variation in wind data with elevation may occur for example, inknown prevailing winds, such as the jet stream or close to the ground.When there are multiple elevations with similar or same wind data, thoseelevations can be eliminated at 200. In the example of FIG. 7, this mayentail disregarding the wind data points 224, 226, 244, and 246. Inother words, when data elements comprise an elevation with associatedmeteorological data, elevations where there are no appreciabledifference in relevant wind data can be eliminated without introducingsignificant error in the estimation of the time of arrival or fuel burn.

Once the redundant wind elements are removed from consideration at 200,variables related to the trade-off between error in time estimation (C1)and fuel burn estimation (C0) are initialized at 202. These variables C0and C1 may be set based upon a user's desired importance of correctlypredicting the time estimation versus the fuel burn. In other words, ifit is considered more important to correctly predict the fuel burn thanthe estimated time of arrival, then C0 may be set at a higher value thanC1.

Once variables have been initialized at 202, a subset of wind elementsof MAX element threshold is selected at 204. The selection of the subsetmay be based on heuristic methods or user defined methods. For example,the chosen elements of the subset may be determined based on having amaximum elevation spread, or a high concentration of elements atelevation ranges known to produce strong winds. The subset selected at204 is then used to generate a wind profile at 206. The generated windprofile can be a set of data with each data set comprising an elevationand related meteorological data at that elevation. The wind profilegeneration 206 may further interpolate between elevation points, orextrapolate beyond the minimum and maximum defined elevation points, oruse any known mathematical technique to estimate the meteorological dataat all elevation levels in which the aircraft 20 can operate based uponthe subset data. A fuel and time cost is then determined for the subsetat 208 based upon the wind profile for the subset. The concept of fuelcost and time cost is described in greater detail above for thedescription of 194. The fuel and time cost for a subset of the data mayalso take into account the guidance behavior of the aircraft for aprofile that the FMS will construct based on the subset only. Forexample, if the trajectory is built assuming only the subset of wind andtemperature data but the actual airmass the aircraft flies throughcontains the full set of winds and temperatures, additional thrust anddrag may be required to compensate for the errors introduced by usingonly the subset of data. These guidance actions will introduceadditional fuel and time costs. It is next determined at 210 if amaximum number of wind subsets have been examined. If not, then themethod returns to step 204 to select the next subset of wind elements.The maximum number of subsets to examine may be based on a fixedpredetermined number. For example, the number of subsets examined maydepend on the computational time at 206 and 208.

If at 210 the maximum number has been examined, then at 212 the windsubset is selected to minimize the combined weighted error or penalty ofthe fuel burn and time. A combined weighted penalty is calculated foreach subset as C0 multiplied by the Fuel_Penalty plus C1 multiplied bythe Time_Penalty (C0*Fuel_Penalty+C1*Time_Penalty). The Fuel_Penalty isthe difference in the fuel cost determined at 194 for the completemeteorological dataset and at 208 for each subset (Fuel_Penalty=FuelCost−Subset Fuel Cost). Similarly, the Time_Penalty is the difference inthe time cost determined at 194 for the complete meteorological datasetand at 208 for each subset (Time_Penalty=Time Cost−Subset Time Cost).The wind data subset with the minimal combined weighted error isselected and stored for use by the FMS or other user of the data,preferably in a non-transitory medium such as a hard disk drive.Optionally, the data set comprising an altitude and correspondingmeteorological data such as tailwind, cross-wind, and temperature can betransmitted to the FMS on board the aircraft 20 via communications link30. It will be understood that any determined or selected subset can betransmitted to an aircraft in flight or on the ground, or transmitted toanother user for the purpose of updating a predicted trajectory of theaircraft.

It should be appreciated that the elements of method 114 can be executedout of order or with variations and not detract from the inventiveconcept disclosed herein. For example, 190 and 192 may be executedconcurrently or in reverse order. Additionally, the method 114 mayinvolve other variables and counters that may need to be initialized,set, reset or otherwise used as commonly known in the art and everyspecific variation is not discussed in the interest of a succinctdescription.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they have structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal languages of the claims.

1. A method of optimizing a descent trajectory of an aircraft comprising the steps of, in a processor: A. receiving a predicted descent trajectory comprising a plurality of points including a start point and an end point; B. receiving meteorological information for data points along the predicted descent trajectory; C. determining a fuel cost and time cost based upon the meteorological data points along the predicted descent trajectory; D. determining if the number of meteorological data points exceeds a predetermined maximum and if the number does not exceed the predetermined maximum, then selecting all of the meteorological data points and proceeding to step K; E. removing redundant meteorological data points from the meteorological data at all of the plurality of points along the predicted descent trajectory; F. selecting a subset of the meteorological data containing the predetermined maximum number of data points from the plurality of wind data points along the predicted descent trajectory; G. generating a wind profile along the predicted descent trajectory using the subset of the meteorological data; H. determining a subset fuel cost and a subset time cost based upon the wind profile and recording the subset data points, the subset fuel cost and subset time cost; I. determining if a predetermined maximum number of subsets have been selected and if the predetermined maximum number of subsets have not been selected, then returning to step F; J. selecting the meteorological data points corresponding to the subset that minimizes the weighted fuel burn and time error; K. storing in a non-transitory medium the selected meteorological data points as the second subset of meteorological data; and L. calculating in the processor an optimized descent trajectory based on the stored second subset.
 2. The method of claim 1 wherein the meteorological data comprises tailwind components and cross-wind components.
 3. The method of claim 2 wherein the tailwind components include wind velocity along the predicted descent trajectory.
 4. The method of claim 1 wherein determining the fuel cost comprises determining a fuel burn of the aircraft during the predicted descent trajectory and determining the time cost comprises determining a time taken to traverse the predicted descent trajectory.
 5. The method of claim 1 wherein removing redundant meteorological data points comprises removing meteorological data at altitudes where the meteorological data is substantially the same as the meteorological data at an adjacent higher altitude and at an adjacent lower altitude.
 6. The method of claim 1 wherein selecting the subset of the meteorological data comprises using a heuristic method.
 7. The method of claim 1 wherein selecting the subset of meteorological data comprises selecting wind data elements in each subset such that no two selected subsets are identical.
 8. The method of claim 1 wherein determining a weighted fuel burn and time error comprises subtracting the subset fuel cost from the fuel cost and multiplying the value by a first predetermined constant and adding the value of a second predetermined constant multiplying the value of the difference between subset time cost and the time cost (C0*(fuel cost−subset fuel cost)+C1*(time cost−subset time cost)).
 9. The method of claim 2 wherein predicted descent trajectory comprises at least one of the dimensions of latitude, longitude, altitude, and time.
 10. The method of claim 1 wherein the meteorological information comprises wind velocity at points along the predicted descent trajectory.
 11. The method of claim 1 further comprising the step of transmitting the second subset to the aircraft instead of storing the subset. 